Infrared Spectra and Ab Initio Calculations for the F-−(CH4)n (n = 1−8) Anion Clusters

Infrared spectra of mass-selected F-−(CH4)n (n = 1−8) clusters are recorded in the CH stretching region (2500−3100 cm-1). Spectra for the n = 1−3 clusters are interpreted with the aid of ab initio calculations at the MP2/6-311++G(2df 2p) level, which suggest that the CH4ligands bind to F- by equivalent, linear hydrogen bonds. Anharmonic frequencies for CH4 and F-−CH4 are determined using the vibrational self-consistent field method with second-order perturbation theory correction. The n = 1 complex is predicted to have a C3v structure with a single CH group hydrogen bonded to F-. Its spectrum exhibits a parallel band associated with a stretching vibration of the hydrogen-bonded CH group that is red-shifted by 380 cm-1 from the ν1 band of free CH4 and a perpendicular band associated with the asymmetric stretching motion of the nonbonded CH groups, slightly red-shifted from the ν3 band of free CH4. As nincreases, additional vibrational bands appear as a result of Fermi resonances between the hydrogen-bonded CH stretching vibrational mode and the 2ν4 overtone and ν2 + ν4combination levels of the methane solvent molecules. For clusters with n ≤ 8, it appears that the CH4 molecules are accommodated in the first solvation shell, each being attached to the F- anion by equivalent hydrogen bonds

Measuring AGN Feedback with the Sunyaev-Zel'dovich Effect

One of the most important and poorly-understood issues in structure formation is the role of outflows driven by active galactic nuclei (AGN). Using large-scale cosmological simulations, we compute the impact of such outflows on the small-scale distribution of the cosmic microwave background (CMB). Like gravitationally-heated structures, AGN outflows induce CMB distortions both through thermal motions and peculiar velocities, by processes known as the thermal and kinetic Sunyaev-Zel'dovich (SZ) effects, respectively. For AGN outflows the thermal SZ effect is dominant, doubling the angular power spectrum on arcminute scales. But the most distinct imprint of AGN feedback is a substantial increase in the thermal SZ distortions around elliptical galaxies, post-starburst ellipticals, and quasars, which is linearly proportional to the outflow energy. While point source subtraction is difficult for quasars, we show that by appropriately stacking microwave measurements around early-type galaxies, the new generation of small-scale microwave telescopes will be able to directly measure AGN feedback at the level important for current theoretical models.Comment: 12 pages, 12 figures, submitted to ApJ (comments welcome

Germline breast cancer susceptibility genes, tumor characteristics, and survival.

BACKGROUND: Mutations in certain genes are known to increase breast cancer risk. We study the relevance of rare protein-truncating variants (PTVs) that may result in loss-of-function in breast cancer susceptibility genes on tumor characteristics and survival in 8852 breast cancer patients of Asian descent. METHODS: Gene panel sequencing was performed for 34 known or suspected breast cancer predisposition genes, of which nine genes (ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, and TP53) were associated with breast cancer risk. Associations between PTV carriership in one or more genes and tumor characteristics were examined using multinomial logistic regression. Ten-year overall survival was estimated using Cox regression models in 6477 breast cancer patients after excluding older patients (≥75years) and stage 0 and IV disease. RESULTS: PTV9genes carriership (n = 690) was significantly associated (p < 0.001) with more aggressive tumor characteristics including high grade (poorly vs well-differentiated, odds ratio [95% confidence interval] 3.48 [2.35-5.17], moderately vs well-differentiated 2.33 [1.56-3.49]), as well as luminal B [HER-] and triple-negative subtypes (vs luminal A 2.15 [1.58-2.92] and 2.85 [2.17-3.73], respectively), adjusted for age at diagnosis, study, and ethnicity. Associations with grade and luminal B [HER2-] subtype remained significant after excluding BRCA1/2 carriers. PTV25genes carriership (n = 289, excluding carriers of the nine genes associated with breast cancer) was not associated with tumor characteristics. However, PTV25genes carriership, but not PTV9genes carriership, was suggested to be associated with worse 10-year overall survival (hazard ratio [CI] 1.63 [1.16-2.28]). CONCLUSIONS: PTV9genes carriership is associated with more aggressive tumors. Variants in other genes might be associated with the survival of breast cancer patients. The finding that PTV carriership is not just associated with higher breast cancer risk, but also more severe and fatal forms of the disease, suggests that genetic testing has the potential to provide additional health information and help healthy individuals make screening decisions

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types.

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals